英文:
How to create a line plot in python, by importing data from excel and using it to create a plot that shares a common X-Axis?
问题
尝试在Python Spyder中创建一个图表。我有Excel中的样本数据，可以导入到Spyder中。我想要将一个列（'Frequency'）作为X轴，将其余的列（'C1，C2，C3，C4'）绘制在Y轴上。我该怎么做？这是Excel中的数据以及Excel中的图表外观（https://i.stack.imgur.com/eRug5.png），图表和数据。
到目前为止，我有这些。下面的这些命令（也在图像中可见）生成一个空图。
data = data.head()df = pd.DataFrame(data, columns=["Frequency","C1", "C2","C3","C4"])df.plot(x = "Frequency", y=["C1", "C2","C3","C4"])
英文:
Trying to create a plot using Python Spyder. I have sample data in excel which I am able to import into Spyder, I want one column ('Frequency') to be the X axis, and the rest of the columns ('C1,C2,C3,C4') to be plotted on the Y axis. How do I do this? This is the data in excel and how the plot looks in excel (https://i.stack.imgur.com/eRug5.png) , the plot and data
This is what I have so far . These commands below (Also seen in the image) give an empty plot.
data = data.head()
#data.plot(kind='line', x='Frequency', y=['C1','C2','C3','C4'])
df = pd.DataFrame(data, columns=["Frequency","C1", "C2","C3","C4"])
df.plot(x = "Frequency",y=["C1", "C2","C3","C4"])
答案1
得分: 0
这是一个示例，您可以更改列名：
import seaborn as snsimport matplotlib.pyplot as pltdf = pd.DataFrame({'X轴':[1,3,5,7,10,20],'col_2':[.4,.5,.4,.5,.5,.4],'col_3':[.7,.8,.9,.4,.2,.3],'col_4':[.1,.3,.5,.7,.1,.0],'col_5':[.5,.3,.6,.9,.2,.4]})dfm = df.melt('X轴', var_name='cols', value_name='vals')g = sns.catplot(x="X轴", y="vals", hue='cols', data=dfm, kind='point')
英文:
Here is an example, you can change columns names:
import seaborn as snsimport matplotlib.pyplot as pltdf = pd.DataFrame({'X_Axis':[1,3,5,7,10,20],'col_2':[.4,.5,.4,.5,.5,.4],'col_3':[.7,.8,.9,.4,.2,.3],'col_4':[.1,.3,.5,.7,.1,.0],'col_5':[.5,.3,.6,.9,.2,.4]})dfm = df.melt('X_Axis', var_name='cols', value_name='vals')g = sns.catplot(x="X_Axis", y="vals", hue='cols', data=dfm, kind='point')
答案2
得分: 0
import pandas as pdimport matplotlib.pyplot as pltpath = r"C:\Users\Alisha.Walia\Desktop\Alisha\SAMPLE.xlsx"data = pd.read_excel(path)dict1 = (data.to_dict()) #print(dict1)Frequency = data["Frequency "].to_list() #print (Frequency)C1 = data["C1"].to_list() #print(C1)C2 = data["C2"].to_list() #print(C2)C3 = data["C3"].to_list() #print(C3)C4 = data["C4"].to_list() #print(C4)plt.plot(Frequency, C1)plt.plot(Frequency, C2)plt.plot(Frequency, C3)plt.plot(Frequency, C4)plt.style.use('ggplot')plt.title('SAMPLE')plt.xlabel('Frequency 20Hz-200MHz')plt.ylabel('Capacitance pF')plt.xlim(5, 500)plt.ylim(-20, 20)plt.legend()plt.show()
英文:
import pandas as pdimport matplotlib.pyplot as pltpath = r"C:\Users\Alisha.Walia\Desktop\Alisha\SAMPLE.xlsx"data = pd.read_excel(path)#df = pd.DataFrame.from_dict(data)#print(df)#prints out data from excl in tabular formatdict1 = (data.to_dict()) #print(dict1)Frequency=data["Frequency "].to_list() #print (Frequency)C1=data["C1"].to_list() #print(C1)C2=data["C2"].to_list() #print(C2)C3=data["C3"].to_list() #print(C3)C4=data["C4"].to_list() #print(C4)plt.plot(Frequency,C1)plt.plot(Frequency,C2)plt.plot(Frequency,C3)plt.plot(Frequency,C4)plt.style.use('ggplot')plt.title('SAMPLE')plt.xlabel('Frequency 20Hz-200MHz')plt.ylabel('Capacitance pF')plt.xlim(5, 500)plt.ylim(-20,20)plt.legend()plt.show()
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